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Whisper Small

This model is a fine-tuned version of openai/whisper-small on the Common Voice + STC Aug 27 + Speechgen dataset. It achieves the following results on the evaluation set:

Loss: 0.0202
Wer: 1.3962

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 3e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 150
training_steps: 3000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0892	0.2047	500	0.0897	6.6898
0.048	0.4093	1000	0.0480	3.4328
0.0379	0.6140	1500	0.0339	2.2033
0.0299	0.8187	2000	0.0269	2.2453
0.0074	1.0233	2500	0.0216	1.4842
0.0055	1.2280	3000	0.0202	1.3962

Framework versions

Transformers 4.42.3
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1

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Safetensors

Model size

0.2B params

Tensor type

F32

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Base model

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Dataset used to train procit006/whisper-small-nl-aug27

Evaluation results

Wer on Common Voice + STC Aug 27 + Speechgen
self-reported

1.396